Meaningful integration of data, analytics and services of computer-based medical systems: The MIDAS touch

Michaela Black, Jonathan Wallace, Debbie Rankin, Paul Carlin, Raymond Bond, Maurice Mulvenna, Brian Cleland, Scott Fischaber, Gorka Epelde, Gorana Nikolic, Juha Pajula, Regina Connolly

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    4 Citations (Scopus)

    Abstract

    The MIDAS consortium is a partnership involving health authorities, and technical big data experts from universities, research institutions, MNCs and SMEs across six EU countries (UK (NI and England), Ireland, Belgium, Finland, Spain and Slovenia), and the USA. The management of big data for 'health in all' poses a significant challenge for health policy makers. This challenge is addressed by the MIDAS project through the development of an integrated solution enabling knowledge liberation from data silos and unification of heterogeneous big data sources that can provide evidence-based actionable information and transform the way care is provided.
    Original languageEnglish
    Title of host publicationIEEE 32nd International Symposium on Computer-Based Medical Systems
    Subtitle of host publicationCBMS 2019
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages104-105
    Number of pages2
    ISBN (Electronic)978-117281-2286-1
    ISBN (Print)978-1-7281-2287-8
    DOIs
    Publication statusPublished - Jun 2019
    MoE publication typeA4 Article in a conference publication
    Event32nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2019: CBMS 2019 - Cordoba, Spain
    Duration: 5 Jun 20197 Jun 2019

    Publication series

    SeriesIEEE International Symposium on Computer-Based Medical Systems
    ISSN2372-918X

    Conference

    Conference32nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2019
    Country/TerritorySpain
    CityCordoba
    Period5/06/197/06/19

    Keywords

    • Big data
    • Data analytics
    • Health policy
    • User-centred design
    • Visualisation

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